[leftmargin=*]
Normal: Train the model with the assumption shown in Figure REF  and simple binary-cross-entropy (BCE) loss.

WBPR [1]}: This is a re-sampling based denoising method, which considers the popular but uninteracted items are highly likely to be real negative.

T-CE [2]}: This is a re-weighting based denoising method, which uses the Truncated BCE to assign zero weights to large-loss examples
with a dynamic threshold in each iteration.

DPI and DVAE: Our proposed denoising methods.

